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Monday 25 – Friday 29 July 2022
2 hours of live teaching per day
11:00 – 13:00 CEST
This course provides a highly interactive online teaching and learning environment, using state-of-the-art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 12 participants so that the teaching team can cater to the specific needs of each individual.
This course presents the relevant measurement methodologies for social and political attitudes:
The course will give you a solid foundation and applied skills in attitude measurement and attitude dynamics evaluation methodologies. You will learn:
3 credits Engage fully with class activities
4 credits Complete a post-class assignment
Camelia Florela Voinea is Associate Professor at the Department of Public Policy, International Relations and Security Studies, University of Bucharest. She gained her PhD from the University of Low Danube, Galati, Romania.
She has developed doctoral studies in Informatic Sciences (Academic Consortium of University of Milan and University of Turin), and Artificial Intelligence (Department of Computer Science, Free University of Brussels).
Camelia's interests include political methodology, interdisciplinary research methods covering computational and simulation modelling of social and political systems, and political culture interdisciplinary research methods.
At the University of Bucharest, she teaches courses on Models of Political Attitudes, Social Choice and Voting Systems, and Statistics and Data Analysis in Political Science.
This course will help you adapt classic attitude models to actual world politics scenarios. We will use data collections and tests from the high-standard publicly available European and international survey and resources on attitude measurement.
The course blends theory and practice by presenting attitude measurement and evaluation case studies based on relevant world political scenarios. It includes offline video recordings and presentations using data analysis, and short demonstrations based on advanced software (Java, Python, and NetLogo).
Social and political attitudes are at the core of research on the relationship between the individual, group, or whole society on the one hand, and the political system, political leadership, governance, and public policy on the other.
Measuring individual and mass attitudes, and evaluating their dynamic evolutions and impact on the dynamics of society and polity helps us anticipate political evolutions in volatile and risky situations, and increase resilience to challenging phenomena.
This course will give you a strategic understanding of, and applied modelling approaches to, attitude measurement and dynamic attitude change evaluation methodologies. You will learn the key concepts underlying the process of attitude measurement and attitude dynamic change evaluation. These often go missing in research methodology seminars, and are rarely discussed in mainstream methods textbooks. Questions to which we will seek answers include:
The course tackles these questions and more. During hands-on sessions, you will put the techniques learned into practice. You'll be able to work on your own data, discuss your research design with the Instructor, and present your analysis plan and outcomes at the Masterclass.
The course combines asynchronous pre-class assignments, such as readings and pre-recorded videos, along with daily two-hour live sessions on Zoom.
Live sessions will focus on conceptual and experimental / applicative components, each illustrated by presentations and short demonstrations. These will include Q&A segments during which you can talk to the Instructor about pre-class assignments, and enquire about areas of interest connected to the content.
To prevent Zoom fatigue and boredom, the course pedagogy includes small-group work, and short, focused tasks using online apps that support collective work and content engagement. For each online session, you will receive hand-outs in advance providing references, resources, and topics of study for group work. These may inspire your choice of subject for the post-class assignment.
This course assumes no previous knowledge of survey research or attitude measurement methodologies but requires basic understanding of statistical data analysis.
Programming knowledge and skills are not compulsory and are not required for the exercises or individual and group assignments. However, they are welcome and appreciated as student’s personal choice for approaching the practice for this course.
